TAMPA, Fla. (Feb. 26, 2020) - Artificial Intelligence might already be a part of daily life from voice-enabled assistants like Siri and Alexa to the behind-the-scenes tool that social media platforms use to decide what users see. But the revolution in machine learning, big data analytics and super-computing means that almost every facet of life and every industry - from health care to finance to energy to national defense - will be guided by artificial intelligence in the future. That's why more than 100 researchers, inventors, educators and industry leaders gathered at the USF Research Park to discuss the emerging frontier in technology and how it can bring researchers and industry together to advance AI and develop today's students as the AI innovators of tomorrow.

The centerpiece of the conversation was USF's Institute for Artificial Intelligence+X, an interdisciplinary effort producing both new forms of AI and new applications: The "X" in AI+X is how this new technology is applied to real world problems. The institute is led by USF College of Engineering Distinguished Professor Lawrence Hall and Professor Sudeep Sarkar, and works to connect AI experts in Engineering with disciplines across campus, including medicine, psychology and education.

Hall told the audience that USF researchers are exploring a wide range of applications, from a "deep learning" effort to understand how information spreads across social networks - and the similarities it might share with infections disease transmission - to automated reasoning tools that would help consumers find loopholes in contracts. "It actually understands contract wording," Hall said of the effort. "When someone tells you you have no warranty in a weird language, it finds it out."

Robots also depend on machine learning to accomplish tasks, he said. One USF project works on helping robots grasp and pick up items. "If you are ever in to having your beer poured by a robot, it can do that," he said. Another tool under development would help a chat bot or AI system like Siri detect emotion in a human voice to better understand the human side of the conversation and respond accordingly.

Sarkar, chair of the Department of Computer Science and Engineering who has developed new AI-enabled tools in computer vision, image processing, and pattern recognition, said some of USF's AI projects in assistive technologies hold promise in helping people with disabilities or the elderly live more independently by anticipating movement in daily activities before the person attempts to make it. USF researchers have designed algorithms that can allow computers to communicate with people who use sign language by "reading" their hand motions.

“As an institute, what we are planning to do is be the clearing house for USF AI research and education. There are lots of bright ideas that we can collaborate with across the campus... We want to solve some real problems.” - USF College of Engineering Professor Sudeep Sarkar.

“We want to do things with greater accuracy, we want to do things more independently. We don’t want to miss things. We want to deal with complexity, particularly genomic complexity. AI is used in all these arenas.” - Dr. Samuel Wickline, USF Health Morsani College of Medicine.

When it comes to applying AI to medicine and the healthcare system, USF faculty and partners such as Tampa General Hospital are already embracing the future. Dr. Samuel Wickline, director of USF Health's Heart Institute told the crowd that AI is bolstering his lab's efforts in developing nanotechnology and molecular imaging in its dual approach to understanding and treating heart disease: Creating better imaging tools to aid in the diagnosis of diseases of the heart and vascular system and then better delivering drugs to treat the ailments.

Wickline's lab collaborates with the labs of leading engineering Professors Hall and Dmitry Goldgof on projects using AI to modernize the painstaking process now conducted by humans of looking for signs of diseases through medical images generated by echocardiograms and ultrasounds to to render a diagnosis. For example, in treating one form of heart disease medical professionals have to measure how well the heart muscle is squeezing. AI helps technicians, who can sometimes miss details in less than perfect images, by detecting that necessary information and filling in the gaps. That also makes exams faster and less expensive to perform, Wickline noted.

AI is also helpful in looking for patterns in heart tissue - which in some cases can help detect which patients are more susceptible to dying from a heart attack - or easing the tedious, laborious work of technicians who exam heart cells through microscopes. And one of the newest frontiers of heart medicine using AI is genomic "fingerprinting" of heart disease to determine which genes are at work in disease progression. Without AI to organize the massive amount of genomic data to understand that mechanism, researchers would not be able to make advances in the prediction, diagnosis and treatment of heart disease.

USF College of Engineering Professor Dmitry Goldgof, vice chair of the Department of Computer Science and Engineering.

Goldgof is collaborating with USF Health researchers in projects focused on medical image analysis, looking at how that can be applied to challenges as different as improving screening for lung cancer, to pressure ulcers to monitoring the pain of newborns in a neonatal intensive care unit, a particularly vexing challenge. Neonatal pain monitoring is something now done by nurses who apply their years of experience to visually monitor an infant for signs of pain, but the system under development would introduce AI to analyze the data collected from a newborn's cries, limb movement, vital signs and facial expressions via a system of cameras and sensors to provide alerts or even automated administration of pain medicines.

“There is a tremendous amount of art in the practice of medicine and the physician-patient relationship. If you could use AI to get closer to perfecting how we make a diagnosis, with more efficiency and more accuracy, that will free physicians up to practice more of the art of taking care of patients." - Dr. Valerie Riddle, USF Morsani College of Medicine.

Dr. Valerie Riddle, associate dean and assistant professor at the USF Morsani College of Medicine and Entrepreneur- in-Residence at the Tampa Bay Technology Incubator at the USF Research Park.

USF Muma College of Business Professor Balaji Padmanabhan is the director of the Center for Analytics and Creativity. He has spent the past two decades conducting research into data mining and machine learning. Dr. Pranab Mohanty is a USF alum who now serves as the Vice President of the Machine Learning and Artificial Intelligence division at Fidelity Investments. Both are exploring the use of AI to build system that solve specific problems - such as chat bots for customer service - but also augment humans in business services to better predict unanticipated consequences of decisions, create fairness and eliminate bias.

Early AI systems learned from pre-planned logic, Padmanabhan said. Now systems are learning from continuous and massive data. Motivating much of the work is the need to solve global problems and advances in other sectors that can be adapted to business systems, he said.

"Think of a system and how it is already built and changing lives, then you can back track and build a system." - Dr. Balaji Padmanabhan, USF Muma College of Business professor and director of the Center for Analytics and Creativity.

The whole idea of the institute is to bring academia and industry close together." - USF College of Engineering Dean Robert Bishop.

Industry is looking to AI to solve persistent problems, as well as push the boundaries of discovery. USF alum Michael Ludlam, who for the past 20 years has worked in supporting national defense and the American intelligence community at Maxar Technologies, said AI helps analysts make sense of the data that advanced systems capture to make the information useful.

“Analysts are overwhelmed, people are overwhelmed with data. How do we give an analyst back their time instead of collecting the data and sorting the data. One of the ways we do that is through machine learning.” - Michael Ludlam, Senior Software Development Manager for Maxar Technologies

David Lukcic, a USF alum whose work helps Tampa Electric use data to better serve energy customers, said advanced meter infrastructure will provide energy companies and customers more information about their energy environment, but it will take AI to help them use that information to bring greater efficiencies and energy sustainability. The future might bring energy meters that can talk to each other, or in California turn every house with a meter into an earthquake sensor, he said.

The future of AI, however, will be in the hands of today's students, all agreed. To those ends, the university and industry will have to work together to get the most out of the unprecedented technological advantages that AI presents.

"That's why we are seeking to bring the application into the classroom and excite our students to see the use of the knowledge for the future.” - Professor Morris Chang, USF College of Engineering's Department of Electrical Engineering.